Introduction

The present study explores the relationship between sleep quality and memory performance in children with autism and within the broader autism phenotype. Previous research has consistently demonstrated that sleep disturbances are prevalent in autistic populations (Richdale & Schreck, 2009; Cohen et al., 2014). However, only a limited number of studies have directly investigated whether poor sleep is associated with memory deficits, which are a prominent concern for this population. Given the significant heterogeneity in memory functioning among autistic individuals, it has been proposed that sleep may play a crucial role in explaining this variability. A more nuanced understanding of the relationship between sleep and memory could enhance the well-being of autistic individuals and contribute to broader theories of cognition and behavior in clinical populations.

To address these aims, this dissertation analyzes quantitatively collected data from a cohort of children, with and without autism, using objective sleep measures (e.g., sleep efficiency, fragmentation index, actual sleep time, and sleep latency), cognitive assessments (WASI Block Design and Vocabulary subtests), autism traits (Autism Spectrum Quotient, AQ), and a range of memory-related outcomes (AMAP subscales). By examining these associations, the study aims to determine whether variability in sleep quality explains individual differences in memory performance and whether autism trait level moderates these effects.

Hypotheses

Method

Participants

Data for this study were collected from children participating in the “Young Scientist Day” event at Kingston University. The sample included children with an autism diagnosis, children exhibiting high autistic traits but without a formal diagnosis, and neurotypical controls, reflecting the broader autism phenotype. Informed consent was obtained from the parents or legal guardians of all participants in accordance with university ethical standards.

Procedure

Event and Setting

The study took place during the Young Scientist Day, a university-sponsored outreach event designed to engage children in science-based activities. Participants and their families were invited to take part in a series of cognitive and behavioral assessments in a controlled, child-friendly environment at Kingston University.

Sleep Data Collection

Cognitive and Memory Assessments

Testing Schedule

Data Analysis

Data from the actigraphy devices and cognitive assessments were collated for statistical analysis. Sleep parameters were averaged across the monitoring period. Group differences and associations between sleep quality, memory performance, and autism trait level were examined using appropriate statistical tests, including correlation and regression analyses. This methodology ensured rigorous, objective measurement of sleep patterns alongside robust cognitive and memory assessment in a real-world community setting.

Results

Hypothesis 1: Sleep Quality and Memory Performance (Overall Sample)

Hypothesis 1 posited a significant positive correlation between objective measures of sleep quality and memory performance in the overall sample of children. This hypothesis received partial support.

Pearson's correlation analyses revealed a statistically significant negative correlation between Sleep-Latency_(mins)and Object_in_context_2_Score, r = -0.415, p = .028. This indicates that longer sleep latency (suggesting poorer sleep initiation) was associated with lower performance on this specific memory task. Additionally, a significant negative correlation was observed between Alien_Object_Config_Memory_Average and Object_in_context_1_Score, r = -0.542, p = .003, suggesting an inverse relationship between these two memory domains.

Regarding subjective measures, a significant negative correlation was found between CSHQ_Total (Child Sleep Habits Questionnaire, where higher scores indicate more sleep problems) and OMQ_total (Observed Memory Questionnaire total), r = -0.472, p = .012. This suggests that greater self-reported sleep problems were associated with lower observed memory scores. Furthermore, CSHQ_Total was positively correlated with AQ_total, r = 0.631, p < .001, indicating that children with higher autistic traits tended to report more sleep difficulties.

No other statistically significant positive correlations were found between the remaining objective sleep measures (Sleep_Efficiency, Fragmentaion_Index, Actual_Sleep_time_(Mins)) and the other objective memory measures (Temporal_Order_Score, Visual_Recognition_Score, Spatial_Tot, Scene_Rec_Score, Object_in_context_1_Score) in the hypothesized positive direction.

Hypothesis 2: Group Differences in Memory Performance

Hypothesis 2 predicted that children with autism and high autistic traits (High AQ group) would exhibit lower scores on certain memory subtests, particularly relational memory, compared to neurotypical controls (Low AQ group). This hypothesis received partial support.

Independent samples t-tests revealed no statistically significant differences between the Low AQ and High AQ groups for Alien_Object_Config_Memory_Average (t(26) = 0.540, p = .594, Cohen's d = 0.204) or any other objective memory subtests (Temporal_Order_Score, Visual_Recognition_Score, Spatial_Tot, Scene_Rec_Score, Object_in_context_1_Score, Object_in_context_2_Score).

However, a statistically significant difference was found for OMQ_total, with the High AQ group (M = 79.71, SD = 9.77) reporting significantly lower observed memory scores compared to the Low AQ group (M = 92.43, SD = 8.79), t(26) = 3.261, p = .003, Cohen's d = 1.234. This indicates a large effect size for subjectively observed memory difficulties in the group with higher autistic traits.

Hypothesis 3: Group Differences in Objective Sleep Quality

Hypothesis 3 stated that children with autism and high autistic traits would demonstrate poorer objective sleep quality (e.g., lower sleep efficiency, higher fragmentation index, longer sleep latency) compared to neurotypical controls. This hypothesis received partial support.

Independent samples t-tests on objective sleep measures revealed no statistically significant differences between the Low AQ and High AQ groups for Sleep_Efficiency (t(26) = 0.637, p = .530, Cohen's d = 0.241), Fragmentaion_Index(t(26) = -0.247, p = .807, Cohen's d = -0.093), Actual_Sleep_time_(Mins) (t(26) = 0.732, p = .471, Cohen's d = 0.277), or Sleep-Latency_(mins) (t(26) = -0.545, p = .590, Cohen's d = -0.206).

Conversely, a statistically significant difference was found for CSHQ_Total (Child Sleep Habits Questionnaire), with the High AQ group (M = 59.21, SD = 12.92) reporting significantly more sleep problems compared to the Low AQ group (M= 42.71, SD = 9.28), t(26) = -3.261, p = .003, Cohen's d = -1.234. This indicates a large effect size for subjectively reported sleep problems in the group with higher autistic traits.

Hypothesis 4: Moderation of Sleep-Memory Relationship by Autism Trait Level

Hypothesis 4 proposed that the relationship between sleep quality and memory performance would be moderated by autism trait level, with sleep quality having a more pronounced impact on memory deficits in children with higher autistic traits. This hypothesis received support for the specific relationship examined.

A linear regression analysis predicting Alien_Object_Config_Memory_Average from Sleep_Efficiency, AQ_total, and their interaction was conducted. The overall model was not statistically significant, F(3, 24) = 2.548, p = .080, R² = 0.242. However, the interaction term Sleep_Efficiency ✻ AQ_total was statistically significant, b = -0.023, SE = 0.010, t = -2.282, p = .032. This indicates that the relationship between Sleep_Efficiency and Alien_Object_Config_Memory_Average is significantly moderated by AQ_total. The negative coefficient suggests that as AQ_total increases, the association between Sleep_Efficiency and Alien_Object_Config_Memory_Averageweakens or becomes more negative, implying that the potential benefits of higher sleep efficiency on relational memory are diminished in children with higher autistic traits. Collinearity diagnostics indicated severe multicollinearity (Condition Index = 209.997), a common issue with interaction terms, though the significance of the interaction term remains interpretable.

Discussion

The present study aimed to investigate the complex interplay between sleep quality, memory performance, and autism trait level in a cohort of children, including those with autism and within the broader autism phenotype. The findings provide nuanced insights into these relationships, offering both support for some hypotheses and unexpected results for others, highlighting the heterogeneity within this population.

Contrary to initial expectations, Hypothesis 1, which predicted a broad positive correlation between objective sleep quality and memory performance across the overall sample, received only partial support. While a direct positive link was largely absent for objective measures, a significant negative correlation between Sleep-Latency_(mins) and Object_in_context_2_Score suggests that difficulties in falling asleep may indeed be detrimental to specific memory functions. More notably, the study found a significant negative correlation between subjective sleep problems (higher CSHQ_Total) and observed memory difficulties (lower OMQ_total), aligning with existing literature that often relies on subjective reports of sleep disturbances and their impact on daily functioning. The strong positive correlation between CSHQ_Total and AQ_total further reinforces the notion that children with higher autistic traits tend to experience more perceived sleep problems. This discrepancy between objective and subjective sleep measures is a critical finding, suggesting that while actigraphy may not capture all aspects of sleep disturbance that impact memory, parental reports (CSHQ) and observed memory (OMQ) may be more sensitive indicators of functional impact in this population.

Hypothesis 2, predicting lower memory scores in the high autistic trait group, also received partial support. While objective memory tasks from the AMAP battery did not reveal significant differences between the Low AQ and High AQgroups, the High AQ group did report significantly lower scores on the OMQ_total. This suggests that while children with higher autistic traits may perform comparably on structured, tablet-based memory assessments, their everyday memory functioning, as observed by caregivers, might be more impaired. This finding underscores the importance of considering both objective and subjective measures when assessing cognitive abilities in neurodevelopmental conditions, as laboratory-based tasks may not fully capture real-world challenges.

Similarly, Hypothesis 3, concerning group differences in sleep quality, was partially supported. Objective actigraphy measures of sleep (Sleep_Efficiency, Fragmentaion_Index, Actual_Sleep_time_(Mins), Sleep-Latency_(mins)) did not significantly differentiate the Low AQ and High AQ groups. This could be due to the relatively small sample size, the specific operationalization of "high AQ" versus a formal diagnosis, or the inherent variability in objective sleep parameters even within clinical populations. However, consistent with Hypothesis 2's findings, the High AQ group reported significantly more sleep problems on the CSHQ_Total. This reinforces the idea that subjective experience of sleep disturbance is a prominent feature in children with higher autistic traits, even if objective measures do not always show a clear distinction from neurotypical peers in this sample. This highlights the potential for a disconnect between objective physiological sleep patterns and the lived experience of sleep quality and its impact.

Perhaps the most compelling finding relates to Hypothesis 4, which posited that autism trait level would moderate the relationship between sleep quality and memory performance. This hypothesis was supported for the specific interaction between Sleep_Efficiency and AQ_total in predicting Alien_Object_Config_Memory_Average. The significant negative interaction term suggests that the beneficial effect of higher sleep efficiency on relational memory is attenuated or even reversed as autistic traits increase. This implies that good sleep quality may not confer the same memory advantages to children with higher autistic traits as it might to those with fewer traits. This finding is crucial for understanding the heterogeneity in memory functioning observed in autistic individuals and suggests that sleep may indeed play a unique role in shaping memory outcomes within the broader autism phenotype. It points towards a more complex, moderated relationship rather than a simple direct effect, providing a nuanced understanding of how sleep influences cognition in this population.

Limitations

Despite these valuable insights, the study has several limitations. The sample size of 28 participants, with 14 in each AQ group, is relatively small, which may limit the statistical power to detect smaller effects and generalize findings to a broader population. The reliance on convenience sampling from a "Young Scientist Day" event might introduce selection bias, as participating families may differ systematically from the general population of children with and without autistic traits. While AQ_Group effectively differentiated participants by trait level, the absence of formal diagnoses for all "High AQ" participants means the findings cannot be directly generalized to clinically diagnosed autism spectrum disorder without caution. Furthermore, the objective sleep data, while valuable, may not capture all aspects of sleep quality relevant to memory, and the 7-day actigraphy period might not fully account for long-term sleep variability. The presence of severe multicollinearity in the moderation analysis, though common, also warrants careful interpretation of individual main effects.

Conclusion

In conclusion, this study provides important insights into the relationship between sleep, memory, and autism traits in children. While broad direct associations between objective sleep quality and memory were largely unsupported, subjective reports highlighted significant sleep difficulties and observed memory impairments in children with higher autistic traits. Crucially, the finding that autism trait level moderates the relationship between sleep efficiency and relational memory suggests a more intricate interaction, where good sleep may not uniformly benefit memory across the autism spectrum. These findings underscore the importance of considering both objective and subjective measures of sleep and memory, and suggest that interventions targeting sleep in autistic populations may need to consider individual differences in autism trait severity to optimize cognitive outcomes. Future research with larger, more diverse samples and longitudinal designs is warranted to further elucidate these complex relationships and inform targeted interventions.

 

Results

Descriptive Statistics

Descriptive Statistics
Sleep_Efficiency
Fragmentaion_Index
Actual_Sleep_time_(Mins)
Sleep-Latency_(mins)
BLOCK_DESIGN T_SCORE
VOCAB_T_SCORE
Alien_Object_Config_Memory_Average
Temporal_Order_Score
Visual_Recognition_Score
Spatial_Tot
Scene_Rec_Score
Object_in_context_1_Score
Object_in_context_2_Score
OMQ_total
CSHQ_Total
AQ_total
  Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ Low AQ High AQ
Valid 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14
Mean 82.886 82.021 25.529 26.000 486.143 475.857 21.071 23.786 52.143 61.071 53.786 59.214 14.179 12.957 5.214 5.214 11.429 11.214 22.143 22.786 9.500 10.071 21.571 22.071 18.143 19.500 110.429 92.429 40.429 47.357 42.714 79.714
Std. Deviation 3.584 3.598 5.725 4.267 42.219 31.329 14.499 11.683 9.773 8.792 9.768 11.403 6.173 5.782 0.579 0.699 0.646 1.051 3.035 1.188 1.787 1.542 2.209 1.439 5.475 3.132 9.280 12.918 4.502 6.428 8.862 20.901
Skewness 0.455 0.072 0.147 0.011 1.016 0.187 1.552 0.085 -0.098 0.487 -0.924 -0.385 0.218 0.804 0.028 -0.321 -0.692 -1.420 -3.261 -1.126 -0.991 -1.605 -0.611 -0.324 -1.507 -1.227 -1.182 -0.269 0.286 -0.467 -0.706 0.869
Std. Error of Skewness 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597 0.597
Kurtosis -0.572 0.097 -1.539 -0.547 2.188 -1.410 3.184 -0.714 -1.119 -0.824 1.666 0.443 -1.000 0.441 0.209 -0.633 -0.252 1.252 11.504 1.060 2.210 2.922 -0.377 0.074 2.342 1.165 0.378 -0.746 -0.535 0.514 -0.036 -0.005
Std. Error of Kurtosis 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154 1.154
Minimum 78.200 75.600 17.900 18.800 429.000 437.000 5.000 4.000 35.000 49.000 30.000 38.000 5.800 5.000 4.000 4.000 10.000 9.000 12.000 20.000 5.000 6.000 17.000 19.000 4.000 12.000 90.000 72.000 34.000 33.000 25.000 56.000
Maximum 90.100 88.500 34.100 33.000 593.000 530.000 60.000 45.000 67.000 77.000 68.000 80.000 25.400 26.000 6.000 6.000 12.000 12.000 24.000 24.000 12.000 12.000 24.000 24.000 24.000 23.000 120.000 113.000 49.000 57.000 55.000 123.000
25th percentile 80.075 80.900 21.075 23.150 465.250 447.250 10.750 15.000 44.000 53.750 50.250 57.000 9.000 9.450 5.000 5.000 11.000 11.000 22.000 22.250 9.000 10.000 20.250 21.000 16.250 18.250 107.250 84.000 37.000 43.250 38.250 62.000
50th percentile 81.950 82.100 24.550 26.000 482.500 478.000 21.000 25.500 54.500 59.500 53.000 59.000 13.700 11.400 5.000 5.000 11.500 11.500 23.000 23.000 10.000 10.500 22.000 22.000 19.500 20.500 114.000 96.500 41.500 47.000 45.000 77.500
75th percentile 85.850 83.625 30.875 28.100 509.250 502.250 24.500 30.750 59.250 65.500 59.500 66.000 19.375 16.625 5.750 6.000 12.000 12.000 23.750 23.750 10.000 11.000 23.750 23.000 22.000 22.000 116.750 98.750 42.750 51.000 47.750 83.500

Boxplots

Sleep_Efficiency

Fragmentaion_Index

Actual_Sleep_time_(Mins)

Sleep-Latency_(mins)

BLOCK_DESIGN T_SCORE

VOCAB_T_SCORE

Alien_Object_Config_Memory_Average

Temporal_Order_Score

Visual_Recognition_Score

Spatial_Tot

Scene_Rec_Score

Object_in_context_1_Score

Object_in_context_2_Score

OMQ_total

CSHQ_Total

AQ_total

Binomial Test

Binomial Test
Variable Level Counts Total Proportion p
Gender Male 19 28 0.679 0.087
  Female 9 28 0.321 0.087
AQ_Group Low AQ 14 28 0.500 1.000
  High AQ 14 28 0.500 1.000
Note.  Proportions tested against value: 0.5.

Correlation

Correlation Table
Pearson
Spearman
      r p rho p
AQ_total - OMQ_total -0.711 *** < .001 -0.642 *** < .001
AQ_total - CSHQ_Total 0.631 *** < .001 0.589 *** < .001
OMQ_total - CSHQ_Total -0.472 * 0.011 -0.437 * 0.020
* p < .05, ** p < .01, *** p < .001

Scatter plots

AQ_total vs. OMQ_total

AQ_total vs. CSHQ_Total

OMQ_total vs. CSHQ_Total

Correlation

Correlation Table
Pearson
Spearman
      r p rho p
Sleep_Efficiency - BLOCK_DESIGN T_SCORE -0.201 0.304 -0.189 0.335
Sleep_Efficiency - VOCAB_T_SCORE -0.320 0.096 -0.310 0.109
Sleep_Efficiency - Alien_Object_Config_Memory_Average -0.198 0.312 -0.250 0.200
Sleep_Efficiency - Temporal_Order_Score -0.032 0.872 -0.018 0.929
Sleep_Efficiency - Visual_Recognition_Score 0.181 0.355 0.202 0.302
Sleep_Efficiency - Spatial_Tot -0.182 0.354 -0.161 0.414
Sleep_Efficiency - Scene_Rec_Score -0.081 0.681 -0.049 0.803
Sleep_Efficiency - Object_in_context_1_Score 0.027 0.890 0.211 0.280
Sleep_Efficiency - Object_in_context_2_Score -0.019 0.922 -0.097 0.623
Sleep_Efficiency - AQ_total -0.152 0.439 -0.142 0.472
Sleep_Efficiency - OMQ_total 0.096 0.626 0.055 0.780
Fragmentaion_Index - BLOCK_DESIGN T_SCORE 0.161 0.413 0.147 0.457
Fragmentaion_Index - VOCAB_T_SCORE 0.283 0.144 0.232 0.235
Fragmentaion_Index - Alien_Object_Config_Memory_Average -0.064 0.748 -0.036 0.856
Fragmentaion_Index - Temporal_Order_Score -0.039 0.844 -0.046 0.817
Fragmentaion_Index - Visual_Recognition_Score 0.040 0.840 0.055 0.780
Fragmentaion_Index - Spatial_Tot 0.279 0.151 0.171 0.384
Fragmentaion_Index - Scene_Rec_Score 0.252 0.195 0.304 0.116
Fragmentaion_Index - Object_in_context_1_Score 0.186 0.343 0.169 0.389
Fragmentaion_Index - Object_in_context_2_Score 0.219 0.263 0.233 0.234
Fragmentaion_Index - AQ_total 0.144 0.465 0.135 0.493
Fragmentaion_Index - OMQ_total -0.199 0.310 -0.183 0.351
Actual_Sleep_time_(Mins) - BLOCK_DESIGN T_SCORE -0.171 0.383 -0.064 0.747
Actual_Sleep_time_(Mins) - VOCAB_T_SCORE 0.033 0.869 0.120 0.544
Actual_Sleep_time_(Mins) - Alien_Object_Config_Memory_Average 0.200 0.308 0.251 0.197
Actual_Sleep_time_(Mins) - Temporal_Order_Score -0.155 0.432 -0.141 0.473
Actual_Sleep_time_(Mins) - Visual_Recognition_Score 0.098 0.620 0.135 0.492
Actual_Sleep_time_(Mins) - Spatial_Tot 0.012 0.952 0.066 0.738
Actual_Sleep_time_(Mins) - Scene_Rec_Score -0.008 0.968 0.070 0.724
Actual_Sleep_time_(Mins) - Object_in_context_1_Score -0.207 0.290 -0.297 0.125
Actual_Sleep_time_(Mins) - Object_in_context_2_Score -0.211 0.281 -0.282 0.145
Actual_Sleep_time_(Mins) - AQ_total -0.216 0.270 -0.168 0.394
Actual_Sleep_time_(Mins) - OMQ_total 0.183 0.351 0.206 0.294
Sleep-Latency_(mins) - BLOCK_DESIGN T_SCORE 0.222 0.257 0.296 0.127
Sleep-Latency_(mins) - VOCAB_T_SCORE 0.057 0.774 0.144 0.464
Sleep-Latency_(mins) - Alien_Object_Config_Memory_Average 0.151 0.443 0.107 0.588
Sleep-Latency_(mins) - Temporal_Order_Score -0.107 0.589 -0.110 0.577
Sleep-Latency_(mins) - Visual_Recognition_Score -0.247 0.205 -0.279 0.151
Sleep-Latency_(mins) - Spatial_Tot 0.119 0.546 0.117 0.554
Sleep-Latency_(mins) - Scene_Rec_Score 0.129 0.511 0.083 0.675
Sleep-Latency_(mins) - Object_in_context_1_Score -0.344 0.073 -0.439 * 0.019
Sleep-Latency_(mins) - Object_in_context_2_Score -0.415 * 0.028 -0.173 0.378
Sleep-Latency_(mins) - AQ_total -0.003 0.989 0.116 0.558
Sleep-Latency_(mins) - OMQ_total 0.098 0.622 -0.008 0.968
Sleep-Latency_(mins) - CSHQ_Total 0.151 0.444 0.181 0.358
BLOCK_DESIGN T_SCORE - AQ_total 0.417 * 0.027 0.394 * 0.038
BLOCK_DESIGN T_SCORE - OMQ_total -0.201 0.306 -0.175 0.372
BLOCK_DESIGN T_SCORE - CSHQ_Total 0.108 0.584 0.097 0.624
VOCAB_T_SCORE - AQ_total 0.337 0.079 0.257 0.187
VOCAB_T_SCORE - OMQ_total -0.092 0.640 -0.030 0.880
VOCAB_T_SCORE - CSHQ_Total 0.217 0.268 0.187 0.340
Alien_Object_Config_Memory_Average - AQ_total -0.162 0.411 -0.214 0.275
Alien_Object_Config_Memory_Average - OMQ_total 0.165 0.402 0.159 0.418
Alien_Object_Config_Memory_Average - CSHQ_Total -0.167 0.395 -0.167 0.396
Temporal_Order_Score - AQ_total 0.205 0.295 0.149 0.448
Temporal_Order_Score - OMQ_total -0.199 0.310 -0.112 0.569
Temporal_Order_Score - CSHQ_Total -0.058 0.771 0.022 0.912
Visual_Recognition_Score - AQ_total 0.142 0.472 0.164 0.405
Visual_Recognition_Score - OMQ_total -0.009 0.966 0.023 0.907
Visual_Recognition_Score - CSHQ_Total 0.284 0.143 0.302 0.119
Spatial_Tot - AQ_total 0.003 0.989 -0.093 0.638
Spatial_Tot - OMQ_total -0.051 0.795 0.265 0.174
Spatial_Tot - CSHQ_Total -0.271 0.163 -0.271 0.164
Scene_Rec_Score - AQ_total 0.032 0.872 0.180 0.360
Scene_Rec_Score - OMQ_total 0.026 0.897 -0.065 0.743
Scene_Rec_Score - CSHQ_Total 0.029 0.885 0.069 0.728
Object_in_context_1_Score - AQ_total 0.258 0.185 0.196 0.316
Object_in_context_1_Score - OMQ_total -0.005 0.978 -0.027 0.893
Object_in_context_1_Score - CSHQ_Total -0.014 0.944 -0.013 0.946
Object_in_context_2_Score - AQ_total 0.123 0.534 0.111 0.574
Object_in_context_2_Score - OMQ_total -0.067 0.735 -0.021 0.917
Object_in_context_2_Score - CSHQ_Total 0.021 0.915 -0.001 0.995
AQ_total - OMQ_total -0.711 *** < .001 -0.642 *** < .001
AQ_total - CSHQ_Total 0.631 *** < .001 0.589 *** < .001
OMQ_total - CSHQ_Total -0.472 * 0.011 -0.437 * 0.020
* p < .05, ** p < .01, *** p < .001

Independent Samples T-Test

Independent Samples T-Test
Test Statistic df p Effect Size SE Effect Size
Alien_Object_Config_Memory_Average Student 0.540 26.000 0.594 0.204 0.380
  Welch 0.540 25.889 0.594 0.204 0.380
  Mann-Whitney 112.500 0.520 0.148 0.219
Temporal_Order_Score Student 0.000 26.000 1.000 0.000 0.378
  Welch 0.000 25.125 1.000 0.000 0.378
  Mann-Whitney 96.500 0.959 -0.015 0.219
Visual_Recognition_Score Student 0.650 26.000 0.521 0.246 0.381
  Welch 0.650 21.601 0.523 0.246 0.381
  Mann-Whitney 102.500 0.839 0.046 0.219
Spatial_Tot Student -0.738 26.000 0.467 -0.279 0.382
  Welch -0.738 16.895 0.471 -0.279 0.382
  Mann-Whitney 91.000 0.755 -0.071 0.219
Scene_Rec_Score Student -0.906 26.000 0.373 -0.342 0.383
  Welch -0.906 25.458 0.374 -0.342 0.383
  Mann-Whitney 72.500 0.238 -0.260 0.219
Object_in_context_1_Score Student -0.710 26.000 0.484 -0.268 0.381
  Welch -0.710 22.353 0.485 -0.268 0.381
  Mann-Whitney 89.000 0.690 -0.092 0.219
Object_in_context_2_Score Student -0.805 26.000 0.428 -0.304 0.382
  Welch -0.805 20.684 0.430 -0.304 0.382
  Mann-Whitney 90.500 0.745 -0.077 0.219
BLOCK_DESIGN T_SCORE Student -2.541 26.000 0.017 -0.961 0.419
  Welch -2.541 25.714 0.017 -0.961 0.419
  Mann-Whitney 54.500 0.048 -0.444 0.219
VOCAB_T_SCORE Student -1.353 26.000 0.188 -0.511 0.390
  Welch -1.353 25.401 0.188 -0.511 0.390
  Mann-Whitney 67.500 0.167 -0.311 0.219
OMQ_total Student 4.234 26.000 < .001 1.600 0.484
  Welch 4.234 23.595 < .001 1.600 0.484
  Mann-Whitney 172.000 < .001 0.755 0.219
Note.  For the Student t-test and Welch t-test, effect size is given by Cohen's d. For the Mann-Whitney test, effect size is given by the rank biserial correlation.

Assumption Checks

Test of Normality (Shapiro-Wilk)
    W p
Alien_Object_Config_Memory_Average Low AQ 0.946 0.501
  High AQ 0.948 0.537
Temporal_Order_Score Low AQ 0.750 0.001
  High AQ 0.806 0.006
Visual_Recognition_Score Low AQ 0.758 0.002
  High AQ 0.721 < .001
Spatial_Tot Low AQ 0.536 < .001
  High AQ 0.849 0.022
Scene_Rec_Score Low AQ 0.902 0.119
  High AQ 0.821 0.009
Object_in_context_1_Score Low AQ 0.912 0.168
  High AQ 0.916 0.193
Object_in_context_2_Score Low AQ 0.861 0.032
  High AQ 0.880 0.058
BLOCK_DESIGN T_SCORE Low AQ 0.941 0.431
  High AQ 0.943 0.461
VOCAB_T_SCORE Low AQ 0.933 0.339
  High AQ 0.945 0.488
OMQ_total Low AQ 0.856 0.026
  High AQ 0.937 0.378
Note.  Significant results suggest a deviation from normality.
Test of Equality of Variances (Brown-Forsythe)
  F df1 df2 p
Alien_Object_Config_Memory_Average 0.192 1 26 0.665
Temporal_Order_Score 0.553 1 26 0.464
Visual_Recognition_Score 1.073 1 26 0.310
Spatial_Tot 0.673 1 26 0.420
Scene_Rec_Score 0.089 1 26 0.768
Object_in_context_1_Score 2.102 1 26 0.159
Object_in_context_2_Score 1.511 1 26 0.230
BLOCK_DESIGN T_SCORE 0.286 1 26 0.597
VOCAB_T_SCORE 0.184 1 26 0.672
OMQ_total 1.133 1 26 0.297

Descriptives

Group Descriptives
  Group N Mean SD SE Coefficient of variation Mean Rank Sum Rank
Alien_Object_Config_Memory_Average Low AQ 14 14.179 6.173 1.650 0.435 15.536 217.500
  High AQ 14 12.957 5.782 1.545 0.446 13.464 188.500
Temporal_Order_Score Low AQ 14 5.214 0.579 0.155 0.111 14.393 201.500
  High AQ 14 5.214 0.699 0.187 0.134 14.607 204.500
Visual_Recognition_Score Low AQ 14 11.429 0.646 0.173 0.057 14.821 207.500
  High AQ 14 11.214 1.051 0.281 0.094 14.179 198.500
Spatial_Tot Low AQ 14 22.143 3.035 0.811 0.137 14.000 196.000
  High AQ 14 22.786 1.188 0.318 0.052 15.000 210.000
Scene_Rec_Score Low AQ 14 9.500 1.787 0.478 0.188 12.679 177.500
  High AQ 14 10.071 1.542 0.412 0.153 16.321 228.500
Object_in_context_1_Score Low AQ 14 21.571 2.209 0.590 0.102 13.857 194.000
  High AQ 14 22.071 1.439 0.385 0.065 15.143 212.000
Object_in_context_2_Score Low AQ 14 18.143 5.475 1.463 0.302 13.964 195.500
  High AQ 14 19.500 3.132 0.837 0.161 15.036 210.500
BLOCK_DESIGN T_SCORE Low AQ 14 52.143 9.773 2.612 0.187 11.393 159.500
  High AQ 14 61.071 8.792 2.350 0.144 17.607 246.500
VOCAB_T_SCORE Low AQ 14 53.786 9.768 2.611 0.182 12.321 172.500
  High AQ 14 59.214 11.403 3.048 0.193 16.679 233.500
OMQ_total Low AQ 14 110.429 9.280 2.480 0.084 19.786 277.000
  High AQ 14 92.429 12.918 3.453 0.140 9.214 129.000

Independent Samples T-Test

Independent Samples T-Test
Test Statistic df p Effect Size SE Effect Size
Sleep_Efficiency Student 0.637 26.000 0.530 0.241 0.381
  Welch 0.637 26.000 0.530 0.241 0.381
  Mann-Whitney 112.500 0.520 0.148 0.219
Fragmentaion_Index Student -0.247 26.000 0.807 -0.093 0.378
  Welch -0.247 24.036 0.807 -0.093 0.378
  Mann-Whitney 88.500 0.679 -0.097 0.219
Actual_Sleep_time_(Mins) Student 0.732 26.000 0.471 0.277 0.382
  Welch 0.732 23.986 0.471 0.277 0.382
  Mann-Whitney 108.500 0.646 0.107 0.219
Sleep-Latency_(mins) Student -0.545 26.000 0.590 -0.206 0.380
  Welch -0.545 24.875 0.590 -0.206 0.380
  Mann-Whitney 75.000 0.301 -0.235 0.219
CSHQ_Total Student -3.303 26.000 0.003 -1.249 0.446
  Welch -3.303 23.278 0.003 -1.249 0.446
  Mann-Whitney 32.500 0.003 -0.668 0.219
Note.  For the Student t-test and Welch t-test, effect size is given by Cohen's d. For the Mann-Whitney test, effect size is given by the rank biserial correlation.

Assumption Checks

Test of Normality (Shapiro-Wilk)
    W p
Sleep_Efficiency Low AQ 0.940 0.424
  High AQ 0.956 0.661
Fragmentaion_Index Low AQ 0.919 0.210
  High AQ 0.966 0.822
Actual_Sleep_time_(Mins) Low AQ 0.920 0.217
  High AQ 0.918 0.209
Sleep-Latency_(mins) Low AQ 0.862 0.032
  High AQ 0.977 0.955
CSHQ_Total Low AQ 0.944 0.472
  High AQ 0.957 0.673
Note.  Significant results suggest a deviation from normality.
Test of Equality of Variances (Brown-Forsythe)
  F df1 df2 p
Sleep_Efficiency 0.058 1 26 0.812
Fragmentaion_Index 2.387 1 26 0.134
Actual_Sleep_time_(Mins) 0.070 1 26 0.793
Sleep-Latency_(mins) 0.051 1 26 0.823
CSHQ_Total 1.463 1 26 0.237

Descriptives

Group Descriptives
  Group N Mean SD SE Coefficient of variation Mean Rank Sum Rank
Sleep_Efficiency Low AQ 14 82.886 3.584 0.958 0.043 15.536 217.500
  High AQ 14 82.021 3.598 0.962 0.044 13.464 188.500
Fragmentaion_Index Low AQ 14 25.529 5.725 1.530 0.224 13.821 193.500
  High AQ 14 26.000 4.267 1.140 0.164 15.179 212.500
Actual_Sleep_time_(Mins) Low AQ 14 486.143 42.219 11.283 0.087 15.250 213.500
  High AQ 14 475.857 31.329 8.373 0.066 13.750 192.500
Sleep-Latency_(mins) Low AQ 14 21.071 14.499 3.875 0.688 12.857 180.000
  High AQ 14 23.786 11.683 3.122 0.491 16.143 226.000
CSHQ_Total Low AQ 14 40.429 4.502 1.203 0.111 9.821 137.500
  High AQ 14 47.357 6.428 1.718 0.136 19.179 268.500

Descriptives Plots

Sleep_Efficiency
Fragmentaion_Index
Actual_Sleep_time_(Mins)
Sleep-Latency_(mins)
CSHQ_Total

Linear Regression

Model Summary - OMQ_total
Model R Adjusted R² RMSE
M₀ 0.000 0.000 0.000 14.346
M₁ 0.721 0.520 0.460 10.539
Note.  M₁ includes CSHQ_Total, AQ_total, CSHQ_Total:AQ_total
ANOVA
Model   Sum of Squares df Mean Square F p
M₁ Regression 2890.995 3 963.665 8.676 < .001
  Residual 2665.862 24 111.078  
  Total 5556.857 27  
Note.  M₁ includes CSHQ_Total, AQ_total, CSHQ_Total:AQ_total
Note.  The intercept model is omitted, as no meaningful information can be shown.
Coefficients
Model   Unstandardized Standard Error Standardized t p
M₀ (Intercept) 101.429 2.711 37.412 < .001
M₁ (Intercept) 92.617 46.767 1.980 0.059
  CSHQ_Total 0.727 1.053 0.329 0.690 0.497
  AQ_total 0.202 0.727 0.345 0.277 0.784
  CSHQ_Total     AQ_total -0.013 0.015 -1.300 -0.837 0.411
Descriptives
  N Mean SD SE
OMQ_total 28 101.429 14.346 2.711
CSHQ_Total 28 43.893 6.488 1.226
AQ_total 28 61.214 24.557 4.641
Collinearity Diagnostics
Variance Proportions
Model Dimension Eigenvalue Condition Index (Intercept) CSHQ_Total AQ_total CSHQ_Total  ✻  AQ_total
M₁ 1 3.842 1.000 0.000 0.000 0.000 0.000
  2 0.147 5.119 0.005 0.002 0.002 0.004
  3 0.011 18.552 0.022 0.062 0.057 0.020
  4 4.644×10-4 90.950 0.974 0.937 0.942 0.976
Note.  The intercept model is omitted, as no meaningful information can be shown.

Residuals vs. Dependent

Q-Q Plot Standardized Residuals

Linear Regression

Model Summary - Alien_Object_Config_Memory_Average
Model R Adjusted R² RMSE
M₀ 0.000 0.000 0.000 5.902
M₁ 0.491 0.242 0.147 5.452
Note.  M₁ includes Sleep_Efficiency, AQ_total, Sleep_Efficiency:AQ_total
ANOVA
Model   Sum of Squares df Mean Square F p
M₁ Regression 227.161 3 75.720 2.548 0.080
  Residual 713.260 24 29.719  
  Total 940.421 27  
Note.  M₁ includes Sleep_Efficiency, AQ_total, Sleep_Efficiency:AQ_total
Note.  The intercept model is omitted, as no meaningful information can be shown.
Coefficients
Model   Unstandardized Standard Error Standardized t p
M₀ (Intercept) 13.568 1.115 12.165 < .001
M₁ (Intercept) -71.662 58.073 -1.234 0.229
  Sleep_Efficiency 1.073 0.703 0.646 1.526 0.140
  AQ_total 1.849 0.832 7.695 2.222 0.036
  Sleep_Efficiency     AQ_total -0.023 0.010 -7.817 -2.282 0.032
Descriptives
  N Mean SD SE
Alien_Object_Config_Memory_Average 28 13.568 5.902 1.115
Sleep_Efficiency 28 82.454 3.551 0.671
AQ_total 28 61.214 24.557 4.641
Collinearity Diagnostics
Variance Proportions
Model Dimension Eigenvalue Condition Index (Intercept) Sleep_Efficiency AQ_total Sleep_Efficiency  ✻  AQ_total
M₁ 1 3.859 1.000 0.000 0.000 0.000 0.000
  2 0.139 5.269 0.001 0.001 0.001 0.001
  3 0.002 46.744 0.043 0.040 0.052 0.055
  4 8.751×10-5 209.997 0.956 0.959 0.948 0.944
Note.  The intercept model is omitted, as no meaningful information can be shown.

Residuals vs. Dependent

Q-Q Plot Standardized Residuals